A meta-heuristic based goal-selection strategy for mobile robot search in an unknown environment
The single-robot search problem in an unknown environment is defined as the problem of finding a stationary object in the environment whose map is not known a priori. Compared to exploration, the only difference lies in goal selection as the objectives of search and exploration are dissimilar, i.e....
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| Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_03050548_v84_n_p178_Kulich |
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todo:paper_03050548_v84_n_p178_Kulich2023-10-03T15:21:25Z A meta-heuristic based goal-selection strategy for mobile robot search in an unknown environment Kulich, M. Miranda-Bront, J.J. Přeučil, L. Graph Search Problem GRASP Mobile robotics Robotic search Traveling Deliveryman Problem Robotics Graph search GRASP Mobile robotic Robotic searches Traveling deliveryman problem Heuristic algorithms The single-robot search problem in an unknown environment is defined as the problem of finding a stationary object in the environment whose map is not known a priori. Compared to exploration, the only difference lies in goal selection as the objectives of search and exploration are dissimilar, i.e. a trajectory that is optimal in exploration does not necessarily minimize the expected value of the time to find an object along it. For this reason, in this paper we extend the preliminary ideas presented in Kulich et al. [1] to a general framework that accounts for the particular characteristics of the search problem. Within this framework, an important decision involved in the determination of the trajectory can be formulated as an instance of the Graph Search Problem (GSP), a generalization of the well-known Traveling Deliveryman Problem (TDP) which has not received much attention in the literature. We developed a tailored Greedy Randomized Adaptive Search Procedure (GRASP) meta-heuristic for the GSP, which generates good quality solutions in very short computing times and is incorporated in the overall framework. The proposed approach produces very good results in a simulation environment, showing that it is feasible from a computational standpoint and the proposed strategy outperforms the standard approaches. © 2016 Elsevier Ltd Fil:Miranda-Bront, J.J. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_03050548_v84_n_p178_Kulich |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
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Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Graph Search Problem GRASP Mobile robotics Robotic search Traveling Deliveryman Problem Robotics Graph search GRASP Mobile robotic Robotic searches Traveling deliveryman problem Heuristic algorithms |
| spellingShingle |
Graph Search Problem GRASP Mobile robotics Robotic search Traveling Deliveryman Problem Robotics Graph search GRASP Mobile robotic Robotic searches Traveling deliveryman problem Heuristic algorithms Kulich, M. Miranda-Bront, J.J. Přeučil, L. A meta-heuristic based goal-selection strategy for mobile robot search in an unknown environment |
| topic_facet |
Graph Search Problem GRASP Mobile robotics Robotic search Traveling Deliveryman Problem Robotics Graph search GRASP Mobile robotic Robotic searches Traveling deliveryman problem Heuristic algorithms |
| description |
The single-robot search problem in an unknown environment is defined as the problem of finding a stationary object in the environment whose map is not known a priori. Compared to exploration, the only difference lies in goal selection as the objectives of search and exploration are dissimilar, i.e. a trajectory that is optimal in exploration does not necessarily minimize the expected value of the time to find an object along it. For this reason, in this paper we extend the preliminary ideas presented in Kulich et al. [1] to a general framework that accounts for the particular characteristics of the search problem. Within this framework, an important decision involved in the determination of the trajectory can be formulated as an instance of the Graph Search Problem (GSP), a generalization of the well-known Traveling Deliveryman Problem (TDP) which has not received much attention in the literature. We developed a tailored Greedy Randomized Adaptive Search Procedure (GRASP) meta-heuristic for the GSP, which generates good quality solutions in very short computing times and is incorporated in the overall framework. The proposed approach produces very good results in a simulation environment, showing that it is feasible from a computational standpoint and the proposed strategy outperforms the standard approaches. © 2016 Elsevier Ltd |
| format |
JOUR |
| author |
Kulich, M. Miranda-Bront, J.J. Přeučil, L. |
| author_facet |
Kulich, M. Miranda-Bront, J.J. Přeučil, L. |
| author_sort |
Kulich, M. |
| title |
A meta-heuristic based goal-selection strategy for mobile robot search in an unknown environment |
| title_short |
A meta-heuristic based goal-selection strategy for mobile robot search in an unknown environment |
| title_full |
A meta-heuristic based goal-selection strategy for mobile robot search in an unknown environment |
| title_fullStr |
A meta-heuristic based goal-selection strategy for mobile robot search in an unknown environment |
| title_full_unstemmed |
A meta-heuristic based goal-selection strategy for mobile robot search in an unknown environment |
| title_sort |
meta-heuristic based goal-selection strategy for mobile robot search in an unknown environment |
| url |
http://hdl.handle.net/20.500.12110/paper_03050548_v84_n_p178_Kulich |
| work_keys_str_mv |
AT kulichm ametaheuristicbasedgoalselectionstrategyformobilerobotsearchinanunknownenvironment AT mirandabrontjj ametaheuristicbasedgoalselectionstrategyformobilerobotsearchinanunknownenvironment AT preucill ametaheuristicbasedgoalselectionstrategyformobilerobotsearchinanunknownenvironment AT kulichm metaheuristicbasedgoalselectionstrategyformobilerobotsearchinanunknownenvironment AT mirandabrontjj metaheuristicbasedgoalselectionstrategyformobilerobotsearchinanunknownenvironment AT preucill metaheuristicbasedgoalselectionstrategyformobilerobotsearchinanunknownenvironment |
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1807322167438737408 |